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Optimisation methods
Gradient descent
Only accepts parameter changes which reduce cost function
Simulated annealing
Will allow increases in cost function with reducing probability
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The inverse problem
Gradient descent can end in a local minima,
whereas simulated annealing will allow, some
“uphill” – like running down a ski slope.
C. Ma et al.
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